Overview

Dataset statistics

Number of variables22
Number of observations2542
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory521.3 KiB
Average record size in memory210.0 B

Variable types

Categorical2
Numeric20

Alerts

seq_name has a high cardinality: 2542 distinct valuesHigh cardinality
seq_name is uniformly distributedUniform
seq_name has unique valuesUnique
A has 35 (1.4%) zerosZeros
R has 34 (1.3%) zerosZeros
N has 73 (2.9%) zerosZeros
D has 56 (2.2%) zerosZeros
C has 104 (4.1%) zerosZeros
E has 35 (1.4%) zerosZeros
Q has 31 (1.2%) zerosZeros
H has 73 (2.9%) zerosZeros
I has 63 (2.5%) zerosZeros
K has 54 (2.1%) zerosZeros
F has 57 (2.2%) zerosZeros
W has 207 (8.1%) zerosZeros
Y has 91 (3.6%) zerosZeros

Reproduction

Analysis started2023-05-22 07:09:33.675821
Analysis finished2023-05-22 07:10:06.096051
Duration32.42 seconds
Software versionpandas-profiling v3.6.6
Download configurationconfig.json

Variables

seq_name
Categorical

HIGH CARDINALITY  UNIFORM  UNIQUE 

Distinct2542
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size39.7 KiB
Negative_0
 
1
Positive_378
 
1
Positive_371
 
1
Positive_372
 
1
Positive_373
 
1
Other values (2537)
2537 

Length

Max length13
Median length12
Mean length12.126672
Min length10

Characters and Unicode

Total characters30826
Distinct characters21
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2542 ?
Unique (%)100.0%

Sample

1st rowNegative_0
2nd rowNegative_1
3rd rowNegative_2
4th rowNegative_3
5th rowNegative_4

Common Values

ValueCountFrequency (%)
Negative_0 1
 
< 0.1%
Positive_378 1
 
< 0.1%
Positive_371 1
 
< 0.1%
Positive_372 1
 
< 0.1%
Positive_373 1
 
< 0.1%
Positive_374 1
 
< 0.1%
Positive_375 1
 
< 0.1%
Positive_376 1
 
< 0.1%
Positive_377 1
 
< 0.1%
Positive_379 1
 
< 0.1%
Other values (2532) 2532
99.6%

Length

2023-05-22T12:40:06.142542image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
negative_0 1
 
< 0.1%
negative_7 1
 
< 0.1%
negative_77 1
 
< 0.1%
negative_9 1
 
< 0.1%
negative_2 1
 
< 0.1%
negative_3 1
 
< 0.1%
negative_4 1
 
< 0.1%
negative_5 1
 
< 0.1%
negative_6 1
 
< 0.1%
negative_8 1
 
< 0.1%
Other values (2532) 2532
99.6%

Most occurring characters

ValueCountFrequency (%)
e 3861
12.5%
i 3765
12.2%
t 2542
 
8.2%
v 2542
 
8.2%
_ 2542
 
8.2%
1 1466
 
4.8%
N 1319
 
4.3%
g 1319
 
4.3%
a 1319
 
4.3%
s 1223
 
4.0%
Other values (11) 8928
29.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 17794
57.7%
Decimal Number 7948
25.8%
Connector Punctuation 2542
 
8.2%
Uppercase Letter 2542
 
8.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1466
18.4%
2 831
10.5%
3 723
9.1%
0 705
8.9%
7 704
8.9%
8 704
8.9%
4 704
8.9%
5 704
8.9%
6 704
8.9%
9 703
8.8%
Lowercase Letter
ValueCountFrequency (%)
e 3861
21.7%
i 3765
21.2%
t 2542
14.3%
v 2542
14.3%
g 1319
 
7.4%
a 1319
 
7.4%
s 1223
 
6.9%
o 1223
 
6.9%
Uppercase Letter
ValueCountFrequency (%)
N 1319
51.9%
P 1223
48.1%
Connector Punctuation
ValueCountFrequency (%)
_ 2542
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 20336
66.0%
Common 10490
34.0%

Most frequent character per script

Common
ValueCountFrequency (%)
_ 2542
24.2%
1 1466
14.0%
2 831
 
7.9%
3 723
 
6.9%
0 705
 
6.7%
7 704
 
6.7%
8 704
 
6.7%
4 704
 
6.7%
5 704
 
6.7%
6 704
 
6.7%
Latin
ValueCountFrequency (%)
e 3861
19.0%
i 3765
18.5%
t 2542
12.5%
v 2542
12.5%
N 1319
 
6.5%
g 1319
 
6.5%
a 1319
 
6.5%
s 1223
 
6.0%
o 1223
 
6.0%
P 1223
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30826
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 3861
12.5%
i 3765
12.2%
t 2542
 
8.2%
v 2542
 
8.2%
_ 2542
 
8.2%
1 1466
 
4.8%
N 1319
 
4.3%
g 1319
 
4.3%
a 1319
 
4.3%
s 1223
 
4.0%
Other values (11) 8928
29.0%

A
Real number (ℝ)

Distinct1888
Distinct (%)74.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.5495712
Minimum0
Maximum33.333
Zeros35
Zeros (%)1.4%
Negative0
Negative (%)0.0%
Memory size39.7 KiB
2023-05-22T12:40:06.245318image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.40915
Q15.683
median7.279
Q39.1425
95-th percentile12.575
Maximum33.333
Range33.333
Interquartile range (IQR)3.4595

Descriptive statistics

Standard deviation2.9199718
Coefficient of variation (CV)0.38677319
Kurtosis3.5453786
Mean7.5495712
Median Absolute Deviation (MAD)1.7025
Skewness0.74585052
Sum19191.01
Variance8.5262351
MonotonicityNot monotonic
2023-05-22T12:40:06.343600image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 35
 
1.4%
7.692 17
 
0.7%
6.667 11
 
0.4%
10 10
 
0.4%
7.143 10
 
0.4%
6.25 9
 
0.4%
8.333 8
 
0.3%
5.882 8
 
0.3%
10.714 8
 
0.3%
9.524 8
 
0.3%
Other values (1878) 2418
95.1%
ValueCountFrequency (%)
0 35
1.4%
0.962 1
 
< 0.1%
1.149 1
 
< 0.1%
1.183 1
 
< 0.1%
1.266 1
 
< 0.1%
1.282 1
 
< 0.1%
1.333 1
 
< 0.1%
1.342 1
 
< 0.1%
1.351 1
 
< 0.1%
1.389 1
 
< 0.1%
ValueCountFrequency (%)
33.333 1
< 0.1%
22.222 1
< 0.1%
20.879 1
< 0.1%
20.769 1
< 0.1%
20.192 1
< 0.1%
20 1
< 0.1%
19.643 1
< 0.1%
18.329 1
< 0.1%
18.31 1
< 0.1%
18.079 1
< 0.1%

R
Real number (ℝ)

Distinct1824
Distinct (%)71.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.6841928
Minimum0
Maximum47.059
Zeros34
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size39.7 KiB
2023-05-22T12:40:06.446159image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.3348
Q14.167
median5.3635
Q36.7965
95-th percentile10.16835
Maximum47.059
Range47.059
Interquartile range (IQR)2.6295

Descriptive statistics

Standard deviation2.6612508
Coefficient of variation (CV)0.46818447
Kurtosis28.158999
Mean5.6841928
Median Absolute Deviation (MAD)1.2905
Skewness2.7282119
Sum14449.218
Variance7.0822558
MonotonicityNot monotonic
2023-05-22T12:40:06.537026image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 34
 
1.3%
5.882 11
 
0.4%
5.263 11
 
0.4%
7.143 9
 
0.4%
6.667 8
 
0.3%
4.167 8
 
0.3%
6.25 8
 
0.3%
4.762 7
 
0.3%
5.556 7
 
0.3%
4 7
 
0.3%
Other values (1814) 2432
95.7%
ValueCountFrequency (%)
0 34
1.3%
0.662 1
 
< 0.1%
0.909 1
 
< 0.1%
0.962 1
 
< 0.1%
1.02 1
 
< 0.1%
1.053 2
 
0.1%
1.064 2
 
0.1%
1.087 2
 
0.1%
1.099 1
 
< 0.1%
1.124 1
 
< 0.1%
ValueCountFrequency (%)
47.059 1
< 0.1%
31.373 1
< 0.1%
20 1
< 0.1%
18.939 1
< 0.1%
18.621 1
< 0.1%
17.822 1
< 0.1%
17.073 1
< 0.1%
16.923 1
< 0.1%
16.667 1
< 0.1%
16.61 1
< 0.1%

N
Real number (ℝ)

Distinct1665
Distinct (%)65.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4583895
Minimum0
Maximum22.222
Zeros73
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size39.7 KiB
2023-05-22T12:40:06.624909image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.8036
Q12.317
median3.391
Q34.412
95-th percentile6.3746
Maximum22.222
Range22.222
Interquartile range (IQR)2.095

Descriptive statistics

Standard deviation1.7769501
Coefficient of variation (CV)0.51380856
Kurtosis6.880932
Mean3.4583895
Median Absolute Deviation (MAD)1.0505
Skewness1.1988095
Sum8791.226
Variance3.1575517
MonotonicityNot monotonic
2023-05-22T12:40:06.711397image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 73
 
2.9%
3.448 15
 
0.6%
3.846 12
 
0.5%
4.348 10
 
0.4%
3.571 9
 
0.4%
3.704 9
 
0.4%
3.39 8
 
0.3%
2.857 8
 
0.3%
5 8
 
0.3%
1.695 8
 
0.3%
Other values (1655) 2382
93.7%
ValueCountFrequency (%)
0 73
2.9%
0.306 1
 
< 0.1%
0.312 1
 
< 0.1%
0.315 1
 
< 0.1%
0.327 1
 
< 0.1%
0.358 1
 
< 0.1%
0.368 1
 
< 0.1%
0.448 1
 
< 0.1%
0.472 1
 
< 0.1%
0.478 1
 
< 0.1%
ValueCountFrequency (%)
22.222 1
< 0.1%
14.286 1
< 0.1%
13.043 1
< 0.1%
12.5 2
0.1%
12.234 1
< 0.1%
11.374 1
< 0.1%
11.111 1
< 0.1%
10.545 1
< 0.1%
10.526 1
< 0.1%
10.27 1
< 0.1%

D
Real number (ℝ)

Distinct1706
Distinct (%)67.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.4497207
Minimum0
Maximum22.222
Zeros56
Zeros (%)2.2%
Negative0
Negative (%)0.0%
Memory size39.7 KiB
2023-05-22T12:40:06.869721image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.37045
Q13.276
median4.512
Q35.544
95-th percentile7.3308
Maximum22.222
Range22.222
Interquartile range (IQR)2.268

Descriptive statistics

Standard deviation1.8631444
Coefficient of variation (CV)0.4187104
Kurtosis4.4028028
Mean4.4497207
Median Absolute Deviation (MAD)1.122
Skewness0.544729
Sum11311.19
Variance3.4713069
MonotonicityNot monotonic
2023-05-22T12:40:06.955821image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 56
 
2.2%
4.762 14
 
0.6%
4.348 14
 
0.6%
5 9
 
0.4%
5.172 8
 
0.3%
5.263 8
 
0.3%
4.878 8
 
0.3%
3.448 8
 
0.3%
4 8
 
0.3%
3.636 7
 
0.3%
Other values (1696) 2402
94.5%
ValueCountFrequency (%)
0 56
2.2%
0.321 1
 
< 0.1%
0.41 1
 
< 0.1%
0.442 1
 
< 0.1%
0.513 1
 
< 0.1%
0.546 1
 
< 0.1%
0.592 2
 
0.1%
0.625 1
 
< 0.1%
0.685 1
 
< 0.1%
0.725 3
 
0.1%
ValueCountFrequency (%)
22.222 1
< 0.1%
14.286 2
0.1%
13.189 1
< 0.1%
12.5 2
0.1%
11.875 1
< 0.1%
11.446 1
< 0.1%
11.409 1
< 0.1%
11.318 1
< 0.1%
11.282 1
< 0.1%
11.176 1
< 0.1%

C
Real number (ℝ)

Distinct1607
Distinct (%)63.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6369658
Minimum0
Maximum32.258
Zeros104
Zeros (%)4.1%
Negative0
Negative (%)0.0%
Memory size39.7 KiB
2023-05-22T12:40:07.043956image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.269
Q11.364
median2.1445
Q33.1495
95-th percentile6.6277
Maximum32.258
Range32.258
Interquartile range (IQR)1.7855

Descriptive statistics

Standard deviation2.4013274
Coefficient of variation (CV)0.91064034
Kurtosis30.227162
Mean2.6369658
Median Absolute Deviation (MAD)0.86
Skewness4.099255
Sum6703.167
Variance5.7663734
MonotonicityNot monotonic
2023-05-22T12:40:07.130553image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 104
 
4.1%
1.887 9
 
0.4%
2.128 8
 
0.3%
2.083 8
 
0.3%
4.348 8
 
0.3%
1.754 8
 
0.3%
1.695 8
 
0.3%
2.857 7
 
0.3%
2.439 7
 
0.3%
1.923 7
 
0.3%
Other values (1597) 2368
93.2%
ValueCountFrequency (%)
0 104
4.1%
0.075 1
 
< 0.1%
0.094 1
 
< 0.1%
0.122 1
 
< 0.1%
0.145 1
 
< 0.1%
0.147 1
 
< 0.1%
0.154 1
 
< 0.1%
0.172 1
 
< 0.1%
0.173 1
 
< 0.1%
0.181 1
 
< 0.1%
ValueCountFrequency (%)
32.258 1
< 0.1%
29.412 1
< 0.1%
27.431 1
< 0.1%
23.077 1
< 0.1%
21.687 1
< 0.1%
20.909 1
< 0.1%
18.987 1
< 0.1%
18.056 2
0.1%
17.241 1
< 0.1%
17.172 1
< 0.1%

E
Real number (ℝ)

Distinct1827
Distinct (%)71.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.9448143
Minimum0
Maximum24.176
Zeros35
Zeros (%)1.4%
Negative0
Negative (%)0.0%
Memory size39.7 KiB
2023-05-22T12:40:07.220519image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.95005
Q14.5165
median5.936
Q37.31625
95-th percentile9.78205
Maximum24.176
Range24.176
Interquartile range (IQR)2.79975

Descriptive statistics

Standard deviation2.4424554
Coefficient of variation (CV)0.41085479
Kurtosis2.8857687
Mean5.9448143
Median Absolute Deviation (MAD)1.391
Skewness0.58995458
Sum15111.718
Variance5.9655886
MonotonicityNot monotonic
2023-05-22T12:40:07.311755image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 35
 
1.4%
5.882 16
 
0.6%
5.556 11
 
0.4%
4.762 9
 
0.4%
7.143 8
 
0.3%
3.226 8
 
0.3%
5 8
 
0.3%
6.667 8
 
0.3%
5.263 8
 
0.3%
3.846 7
 
0.3%
Other values (1817) 2424
95.4%
ValueCountFrequency (%)
0 35
1.4%
0.485 1
 
< 0.1%
0.578 1
 
< 0.1%
0.654 1
 
< 0.1%
0.714 1
 
< 0.1%
0.725 1
 
< 0.1%
0.758 1
 
< 0.1%
0.87 1
 
< 0.1%
0.957 1
 
< 0.1%
0.971 1
 
< 0.1%
ValueCountFrequency (%)
24.176 1
< 0.1%
20 1
< 0.1%
18.75 1
< 0.1%
17.687 1
< 0.1%
17.391 1
< 0.1%
16.901 1
< 0.1%
16.402 1
< 0.1%
16.25 1
< 0.1%
15.289 1
< 0.1%
15.193 1
< 0.1%

Q
Real number (ℝ)

Distinct1700
Distinct (%)66.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.2075555
Minimum0
Maximum29.114
Zeros31
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size39.7 KiB
2023-05-22T12:40:07.400556image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.695
Q13.0935
median3.9975
Q35.03775
95-th percentile7.22835
Maximum29.114
Range29.114
Interquartile range (IQR)1.94425

Descriptive statistics

Standard deviation1.9326241
Coefficient of variation (CV)0.4593223
Kurtosis17.218033
Mean4.2075555
Median Absolute Deviation (MAD)0.9675
Skewness2.3203646
Sum10695.606
Variance3.7350358
MonotonicityNot monotonic
2023-05-22T12:40:07.486091image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 31
 
1.2%
5 12
 
0.5%
3.846 11
 
0.4%
4.348 11
 
0.4%
4.167 10
 
0.4%
3.226 10
 
0.4%
4.651 9
 
0.4%
3.125 9
 
0.4%
4 8
 
0.3%
3.333 8
 
0.3%
Other values (1690) 2423
95.3%
ValueCountFrequency (%)
0 31
1.2%
0.543 1
 
< 0.1%
0.606 1
 
< 0.1%
0.685 1
 
< 0.1%
0.704 1
 
< 0.1%
0.709 1
 
< 0.1%
0.8 1
 
< 0.1%
0.802 1
 
< 0.1%
0.84 1
 
< 0.1%
0.87 1
 
< 0.1%
ValueCountFrequency (%)
29.114 1
 
< 0.1%
17.686 1
 
< 0.1%
17.241 1
 
< 0.1%
16.667 5
0.2%
15.789 1
 
< 0.1%
14.754 1
 
< 0.1%
13.699 1
 
< 0.1%
12.5 2
 
0.1%
11.957 1
 
< 0.1%
11.876 1
 
< 0.1%

G
Real number (ℝ)

Distinct1850
Distinct (%)72.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.3463194
Minimum0
Maximum46.474
Zeros16
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size39.7 KiB
2023-05-22T12:40:07.575146image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.6045
Q15.556
median7.035
Q38.549
95-th percentile11.58975
Maximum46.474
Range46.474
Interquartile range (IQR)2.993

Descriptive statistics

Standard deviation3.4538118
Coefficient of variation (CV)0.4701418
Kurtosis34.877105
Mean7.3463194
Median Absolute Deviation (MAD)1.502
Skewness4.2627874
Sum18674.344
Variance11.928816
MonotonicityNot monotonic
2023-05-22T12:40:07.661650image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 16
 
0.6%
5.882 14
 
0.6%
6.25 14
 
0.6%
7.692 11
 
0.4%
5.556 10
 
0.4%
7.407 9
 
0.4%
5 7
 
0.3%
7.143 7
 
0.3%
6.667 7
 
0.3%
10 7
 
0.3%
Other values (1840) 2440
96.0%
ValueCountFrequency (%)
0 16
0.6%
0.549 1
 
< 0.1%
1.017 1
 
< 0.1%
1.058 1
 
< 0.1%
1.075 1
 
< 0.1%
1.266 1
 
< 0.1%
1.307 1
 
< 0.1%
1.351 1
 
< 0.1%
1.449 1
 
< 0.1%
1.471 1
 
< 0.1%
ValueCountFrequency (%)
46.474 1
< 0.1%
43.21 1
< 0.1%
42.222 1
< 0.1%
38.889 1
< 0.1%
38.835 1
< 0.1%
38.028 1
< 0.1%
36.923 1
< 0.1%
36.207 1
< 0.1%
35.714 1
< 0.1%
35.443 1
< 0.1%

H
Real number (ℝ)

Distinct1538
Distinct (%)60.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4714213
Minimum0
Maximum30
Zeros73
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size39.7 KiB
2023-05-22T12:40:07.747118image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.6291
Q11.64625
median2.3445
Q33.0985
95-th percentile4.48275
Maximum30
Range30
Interquartile range (IQR)1.45225

Descriptive statistics

Standard deviation1.4740827
Coefficient of variation (CV)0.59645139
Kurtosis72.856093
Mean2.4714213
Median Absolute Deviation (MAD)0.727
Skewness4.9931205
Sum6282.353
Variance2.1729198
MonotonicityNot monotonic
2023-05-22T12:40:07.833102image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 73
 
2.9%
3.333 16
 
0.6%
2.857 12
 
0.5%
2.778 11
 
0.4%
2.128 10
 
0.4%
1.923 9
 
0.4%
2.5 9
 
0.4%
4 9
 
0.4%
2.564 9
 
0.4%
1.961 8
 
0.3%
Other values (1528) 2376
93.5%
ValueCountFrequency (%)
0 73
2.9%
0.231 1
 
< 0.1%
0.309 1
 
< 0.1%
0.321 1
 
< 0.1%
0.332 1
 
< 0.1%
0.339 1
 
< 0.1%
0.355 1
 
< 0.1%
0.379 1
 
< 0.1%
0.382 1
 
< 0.1%
0.397 1
 
< 0.1%
ValueCountFrequency (%)
30 1
< 0.1%
25 1
< 0.1%
13.725 1
< 0.1%
12.571 1
< 0.1%
11.765 1
< 0.1%
11.111 1
< 0.1%
10.169 1
< 0.1%
10.072 1
< 0.1%
9.15 1
< 0.1%
9.091 1
< 0.1%

I
Real number (ℝ)

Distinct1818
Distinct (%)71.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.5049552
Minimum0
Maximum16.667
Zeros63
Zeros (%)2.5%
Negative0
Negative (%)0.0%
Memory size39.7 KiB
2023-05-22T12:40:07.924180image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.03265
Q12.985
median4.504
Q35.9105
95-th percentile7.9489
Maximum16.667
Range16.667
Interquartile range (IQR)2.9255

Descriptive statistics

Standard deviation2.1713877
Coefficient of variation (CV)0.48199985
Kurtosis0.7927007
Mean4.5049552
Median Absolute Deviation (MAD)1.463
Skewness0.37511766
Sum11451.596
Variance4.7149246
MonotonicityNot monotonic
2023-05-22T12:40:08.013378image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 63
 
2.5%
5.263 12
 
0.5%
7.143 12
 
0.5%
5.882 10
 
0.4%
3.448 9
 
0.4%
6.25 9
 
0.4%
2.941 9
 
0.4%
4.348 9
 
0.4%
4.167 8
 
0.3%
4.762 8
 
0.3%
Other values (1808) 2393
94.1%
ValueCountFrequency (%)
0 63
2.5%
0.238 1
 
< 0.1%
0.339 1
 
< 0.1%
0.427 1
 
< 0.1%
0.457 1
 
< 0.1%
0.481 1
 
< 0.1%
0.485 1
 
< 0.1%
0.488 1
 
< 0.1%
0.495 1
 
< 0.1%
0.518 1
 
< 0.1%
ValueCountFrequency (%)
16.667 1
< 0.1%
15.789 1
< 0.1%
13.397 1
< 0.1%
13.043 1
< 0.1%
12.903 1
< 0.1%
12.832 1
< 0.1%
12.712 1
< 0.1%
12.5 1
< 0.1%
11.538 1
< 0.1%
11.458 1
< 0.1%

L
Real number (ℝ)

Distinct1938
Distinct (%)76.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.290201
Minimum0
Maximum25.641
Zeros20
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size39.7 KiB
2023-05-22T12:40:08.106381image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5.5302
Q18.4015
median10.041
Q312.02825
95-th percentile15.94135
Maximum25.641
Range25.641
Interquartile range (IQR)3.62675

Descriptive statistics

Standard deviation3.2308102
Coefficient of variation (CV)0.31396961
Kurtosis1.5395886
Mean10.290201
Median Absolute Deviation (MAD)1.806
Skewness0.29712105
Sum26157.69
Variance10.438135
MonotonicityNot monotonic
2023-05-22T12:40:08.266562image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20
 
0.8%
10 17
 
0.7%
12.5 15
 
0.6%
9.091 13
 
0.5%
7.692 12
 
0.5%
11.111 11
 
0.4%
9.524 9
 
0.4%
7.143 9
 
0.4%
11.538 7
 
0.3%
13.333 7
 
0.3%
Other values (1928) 2422
95.3%
ValueCountFrequency (%)
0 20
0.8%
1.183 1
 
< 0.1%
1.205 1
 
< 0.1%
1.37 1
 
< 0.1%
1.374 1
 
< 0.1%
1.695 1
 
< 0.1%
1.724 2
 
0.1%
1.786 1
 
< 0.1%
1.887 1
 
< 0.1%
1.923 1
 
< 0.1%
ValueCountFrequency (%)
25.641 1
< 0.1%
25 1
< 0.1%
24.138 1
< 0.1%
23.469 1
< 0.1%
23.03 1
< 0.1%
22.656 1
< 0.1%
22.613 1
< 0.1%
21.875 1
< 0.1%
20.988 1
< 0.1%
20.833 2
0.1%

K
Real number (ℝ)

Distinct1850
Distinct (%)72.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.0311314
Minimum0
Maximum22.034
Zeros54
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size39.7 KiB
2023-05-22T12:40:08.356019image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.2312
Q13.2705
median4.839
Q36.52025
95-th percentile9.4828
Maximum22.034
Range22.034
Interquartile range (IQR)3.24975

Descriptive statistics

Standard deviation2.5985144
Coefficient of variation (CV)0.5164871
Kurtosis2.5465551
Mean5.0311314
Median Absolute Deviation (MAD)1.613
Skewness0.89108768
Sum12789.136
Variance6.7522773
MonotonicityNot monotonic
2023-05-22T12:40:08.443442image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 54
 
2.1%
3.846 11
 
0.4%
7.143 11
 
0.4%
6.25 11
 
0.4%
2.5 9
 
0.4%
4.348 9
 
0.4%
11.111 8
 
0.3%
6.667 7
 
0.3%
4.167 7
 
0.3%
2.381 7
 
0.3%
Other values (1840) 2408
94.7%
ValueCountFrequency (%)
0 54
2.1%
0.249 1
 
< 0.1%
0.386 1
 
< 0.1%
0.426 1
 
< 0.1%
0.448 1
 
< 0.1%
0.476 1
 
< 0.1%
0.518 2
 
0.1%
0.521 1
 
< 0.1%
0.529 1
 
< 0.1%
0.536 1
 
< 0.1%
ValueCountFrequency (%)
22.034 1
< 0.1%
20.755 1
< 0.1%
18.182 1
< 0.1%
17.516 1
< 0.1%
17.262 1
< 0.1%
17.143 1
< 0.1%
17.105 1
< 0.1%
16.304 1
< 0.1%
16.176 1
< 0.1%
16.014 1
< 0.1%

M
Real number (ℝ)

Distinct1478
Distinct (%)58.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3996825
Minimum0
Maximum13.836
Zeros20
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size39.7 KiB
2023-05-22T12:40:08.531002image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.8934
Q11.63
median2.286
Q32.98125
95-th percentile4.225
Maximum13.836
Range13.836
Interquartile range (IQR)1.35125

Descriptive statistics

Standard deviation1.1656431
Coefficient of variation (CV)0.48574889
Kurtosis11.561157
Mean2.3996825
Median Absolute Deviation (MAD)0.671
Skewness1.9601712
Sum6099.993
Variance1.3587239
MonotonicityNot monotonic
2023-05-22T12:40:08.616577image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20
 
0.8%
2.564 14
 
0.6%
2.5 12
 
0.5%
1.389 12
 
0.5%
2.381 11
 
0.4%
2.941 10
 
0.4%
2.439 10
 
0.4%
1.786 10
 
0.4%
1.695 9
 
0.4%
1.724 9
 
0.4%
Other values (1468) 2425
95.4%
ValueCountFrequency (%)
0 20
0.8%
0.237 1
 
< 0.1%
0.249 1
 
< 0.1%
0.285 1
 
< 0.1%
0.321 1
 
< 0.1%
0.358 1
 
< 0.1%
0.368 1
 
< 0.1%
0.377 1
 
< 0.1%
0.382 1
 
< 0.1%
0.402 1
 
< 0.1%
ValueCountFrequency (%)
13.836 1
< 0.1%
12.658 1
< 0.1%
11.765 1
< 0.1%
11.111 1
< 0.1%
10.377 1
< 0.1%
10.204 1
< 0.1%
8.947 1
< 0.1%
8.824 1
< 0.1%
8.696 1
< 0.1%
7.619 1
< 0.1%

F
Real number (ℝ)

Distinct1675
Distinct (%)65.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9632046
Minimum0
Maximum15.263
Zeros57
Zeros (%)2.2%
Negative0
Negative (%)0.0%
Memory size39.7 KiB
2023-05-22T12:40:08.709011image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.198
Q12.81125
median3.8365
Q34.983
95-th percentile7.11295
Maximum15.263
Range15.263
Interquartile range (IQR)2.17175

Descriptive statistics

Standard deviation1.8235068
Coefficient of variation (CV)0.46010918
Kurtosis1.8744821
Mean3.9632046
Median Absolute Deviation (MAD)1.0815
Skewness0.66479956
Sum10074.466
Variance3.325177
MonotonicityNot monotonic
2023-05-22T12:40:08.796933image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 57
 
2.2%
4.167 16
 
0.6%
4 12
 
0.5%
3.226 9
 
0.4%
3.077 8
 
0.3%
3.333 8
 
0.3%
3.774 7
 
0.3%
4.444 7
 
0.3%
3.03 7
 
0.3%
3.448 7
 
0.3%
Other values (1665) 2404
94.6%
ValueCountFrequency (%)
0 57
2.2%
0.202 1
 
< 0.1%
0.339 1
 
< 0.1%
0.358 1
 
< 0.1%
0.375 1
 
< 0.1%
0.418 1
 
< 0.1%
0.455 1
 
< 0.1%
0.476 1
 
< 0.1%
0.481 1
 
< 0.1%
0.485 1
 
< 0.1%
ValueCountFrequency (%)
15.263 1
< 0.1%
13.514 1
< 0.1%
13.115 1
< 0.1%
12.5 1
< 0.1%
11.538 1
< 0.1%
11.475 1
< 0.1%
11.458 1
< 0.1%
11.111 1
< 0.1%
10.891 1
< 0.1%
10.769 1
< 0.1%

P
Real number (ℝ)

Distinct1845
Distinct (%)72.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.3956755
Minimum0
Maximum42.623
Zeros17
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size39.7 KiB
2023-05-22T12:40:08.893357image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.74115
Q14.469
median5.736
Q37.627
95-th percentile12.212
Maximum42.623
Range42.623
Interquartile range (IQR)3.158

Descriptive statistics

Standard deviation3.401415
Coefficient of variation (CV)0.53183045
Kurtosis23.736086
Mean6.3956755
Median Absolute Deviation (MAD)1.487
Skewness3.2609004
Sum16257.807
Variance11.569624
MonotonicityNot monotonic
2023-05-22T12:40:08.977712image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 17
 
0.7%
6.667 14
 
0.6%
5.882 11
 
0.4%
4.762 10
 
0.4%
5.556 10
 
0.4%
7.143 9
 
0.4%
5 8
 
0.3%
11.111 8
 
0.3%
4.167 8
 
0.3%
6.897 8
 
0.3%
Other values (1835) 2439
95.9%
ValueCountFrequency (%)
0 17
0.7%
0.532 1
 
< 0.1%
0.699 1
 
< 0.1%
0.952 1
 
< 0.1%
0.971 1
 
< 0.1%
0.98 1
 
< 0.1%
1.042 1
 
< 0.1%
1.053 1
 
< 0.1%
1.111 1
 
< 0.1%
1.176 1
 
< 0.1%
ValueCountFrequency (%)
42.623 1
< 0.1%
39.726 1
< 0.1%
38.889 2
0.1%
37.5 2
0.1%
36.111 1
< 0.1%
25.157 1
< 0.1%
22.485 1
< 0.1%
22.222 2
0.1%
21.053 1
< 0.1%
20.096 1
< 0.1%

S
Real number (ℝ)

Distinct1849
Distinct (%)72.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.5065378
Minimum0
Maximum30.769
Zeros12
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size39.7 KiB
2023-05-22T12:40:09.064006image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.0251
Q15.8175
median7.1815
Q38.7735
95-th percentile12.30275
Maximum30.769
Range30.769
Interquartile range (IQR)2.956

Descriptive statistics

Standard deviation2.6567391
Coefficient of variation (CV)0.35392336
Kurtosis4.9703749
Mean7.5065378
Median Absolute Deviation (MAD)1.4675
Skewness1.1997003
Sum19081.619
Variance7.0582625
MonotonicityNot monotonic
2023-05-22T12:40:09.150541image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.25 13
 
0.5%
0 12
 
0.5%
8.333 11
 
0.4%
11.111 11
 
0.4%
5 10
 
0.4%
7.692 10
 
0.4%
10.294 8
 
0.3%
7.143 8
 
0.3%
7.018 7
 
0.3%
7.059 7
 
0.3%
Other values (1839) 2445
96.2%
ValueCountFrequency (%)
0 12
0.5%
1.429 1
 
< 0.1%
1.471 1
 
< 0.1%
1.481 1
 
< 0.1%
1.6 1
 
< 0.1%
1.639 1
 
< 0.1%
1.681 1
 
< 0.1%
1.724 1
 
< 0.1%
1.786 1
 
< 0.1%
1.852 1
 
< 0.1%
ValueCountFrequency (%)
30.769 1
< 0.1%
25.253 1
< 0.1%
23.077 1
< 0.1%
21.446 1
< 0.1%
20.163 1
< 0.1%
20 1
< 0.1%
19.481 1
< 0.1%
18.433 1
< 0.1%
18.421 1
< 0.1%
18.116 1
< 0.1%

T
Real number (ℝ)

Distinct1676
Distinct (%)65.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.3301939
Minimum0
Maximum29.431
Zeros23
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size39.7 KiB
2023-05-22T12:40:09.242546image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.586
Q14.23825
median5.1805
Q36.17475
95-th percentile8.30275
Maximum29.431
Range29.431
Interquartile range (IQR)1.9365

Descriptive statistics

Standard deviation2.0250557
Coefficient of variation (CV)0.37992158
Kurtosis17.319826
Mean5.3301939
Median Absolute Deviation (MAD)0.964
Skewness2.2044193
Sum13549.353
Variance4.1008506
MonotonicityNot monotonic
2023-05-22T12:40:09.327982image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 23
 
0.9%
6.667 14
 
0.6%
5.556 10
 
0.4%
5 10
 
0.4%
5.263 10
 
0.4%
6.25 9
 
0.4%
4.615 9
 
0.4%
3.571 9
 
0.4%
4.762 9
 
0.4%
5.882 8
 
0.3%
Other values (1666) 2431
95.6%
ValueCountFrequency (%)
0 23
0.9%
0.714 1
 
< 0.1%
0.8 1
 
< 0.1%
0.909 1
 
< 0.1%
0.962 1
 
< 0.1%
0.971 1
 
< 0.1%
1 1
 
< 0.1%
1.02 1
 
< 0.1%
1.081 1
 
< 0.1%
1.205 2
 
0.1%
ValueCountFrequency (%)
29.431 1
< 0.1%
25 1
< 0.1%
20.982 1
< 0.1%
20.228 1
< 0.1%
20 1
< 0.1%
16.827 1
< 0.1%
16.262 1
< 0.1%
16.244 1
< 0.1%
16.092 1
< 0.1%
16.026 1
< 0.1%

W
Real number (ℝ)

Distinct1401
Distinct (%)55.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4807502
Minimum0
Maximum9.804
Zeros207
Zeros (%)8.1%
Negative0
Negative (%)0.0%
Memory size39.7 KiB
2023-05-22T12:40:09.419599image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.79125
median1.343
Q31.99575
95-th percentile3.333
Maximum9.804
Range9.804
Interquartile range (IQR)1.2045

Descriptive statistics

Standard deviation1.025822
Coefficient of variation (CV)0.6927718
Kurtosis3.7313896
Mean1.4807502
Median Absolute Deviation (MAD)0.5995
Skewness1.2413195
Sum3764.067
Variance1.0523107
MonotonicityNot monotonic
2023-05-22T12:40:09.508860image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 207
 
8.1%
1.724 10
 
0.4%
1 9
 
0.4%
2.128 9
 
0.4%
1.695 8
 
0.3%
1.754 8
 
0.3%
1.786 8
 
0.3%
0.82 8
 
0.3%
1.429 7
 
0.3%
2.381 7
 
0.3%
Other values (1391) 2261
88.9%
ValueCountFrequency (%)
0 207
8.1%
0.128 1
 
< 0.1%
0.164 2
 
0.1%
0.167 1
 
< 0.1%
0.174 1
 
< 0.1%
0.176 1
 
< 0.1%
0.181 1
 
< 0.1%
0.194 1
 
< 0.1%
0.196 1
 
< 0.1%
0.198 1
 
< 0.1%
ValueCountFrequency (%)
9.804 1
< 0.1%
7.692 1
< 0.1%
7.317 1
< 0.1%
6.667 1
< 0.1%
6.226 1
< 0.1%
6.173 1
< 0.1%
5.941 1
< 0.1%
5.49 1
< 0.1%
5.455 1
< 0.1%
5.405 1
< 0.1%

Y
Real number (ℝ)

Distinct1612
Distinct (%)63.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.9751987
Minimum0
Maximum32.143
Zeros91
Zeros (%)3.6%
Negative0
Negative (%)0.0%
Memory size39.7 KiB
2023-05-22T12:40:09.596817image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.55615
Q11.869
median2.854
Q33.765
95-th percentile5.4039
Maximum32.143
Range32.143
Interquartile range (IQR)1.896

Descriptive statistics

Standard deviation2.0785005
Coefficient of variation (CV)0.69860898
Kurtosis47.052908
Mean2.9751987
Median Absolute Deviation (MAD)0.937
Skewness4.9391485
Sum7562.955
Variance4.3201643
MonotonicityNot monotonic
2023-05-22T12:40:09.683913image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 91
 
3.6%
3.704 10
 
0.4%
3.226 9
 
0.4%
2.128 9
 
0.4%
1.695 8
 
0.3%
3.846 8
 
0.3%
5 8
 
0.3%
2.174 7
 
0.3%
2.703 7
 
0.3%
1.724 7
 
0.3%
Other values (1602) 2378
93.5%
ValueCountFrequency (%)
0 91
3.6%
0.135 1
 
< 0.1%
0.207 1
 
< 0.1%
0.218 1
 
< 0.1%
0.249 1
 
< 0.1%
0.269 1
 
< 0.1%
0.339 2
 
0.1%
0.348 1
 
< 0.1%
0.351 1
 
< 0.1%
0.358 1
 
< 0.1%
ValueCountFrequency (%)
32.143 1
< 0.1%
24.615 1
< 0.1%
24.194 1
< 0.1%
23.611 1
< 0.1%
23.457 1
< 0.1%
22.535 1
< 0.1%
22.414 1
< 0.1%
20.635 1
< 0.1%
20 1
< 0.1%
19.417 1
< 0.1%

V
Real number (ℝ)

Distinct1785
Distinct (%)70.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.3735087
Minimum0
Maximum30
Zeros24
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size39.7 KiB
2023-05-22T12:40:09.846605image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.9763
Q15.125
median6.383
Q37.639
95-th percentile9.5987
Maximum30
Range30
Interquartile range (IQR)2.514

Descriptive statistics

Standard deviation2.1591384
Coefficient of variation (CV)0.33876763
Kurtosis8.7308635
Mean6.3735087
Median Absolute Deviation (MAD)1.258
Skewness0.81747063
Sum16201.459
Variance4.6618786
MonotonicityNot monotonic
2023-05-22T12:40:09.935470image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 24
 
0.9%
7.143 16
 
0.6%
6.452 14
 
0.6%
4.348 11
 
0.4%
5.085 10
 
0.4%
5.556 10
 
0.4%
7.692 10
 
0.4%
6.667 10
 
0.4%
6.25 9
 
0.4%
5 9
 
0.4%
Other values (1775) 2419
95.2%
ValueCountFrequency (%)
0 24
0.9%
0.725 1
 
< 0.1%
0.746 1
 
< 0.1%
0.806 1
 
< 0.1%
0.862 1
 
< 0.1%
0.885 1
 
< 0.1%
0.909 1
 
< 0.1%
0.971 1
 
< 0.1%
1.01 1
 
< 0.1%
1.19 3
 
0.1%
ValueCountFrequency (%)
30 1
< 0.1%
22.222 2
0.1%
20 1
< 0.1%
15.385 1
< 0.1%
15 1
< 0.1%
14.516 1
< 0.1%
14.286 1
< 0.1%
12.981 1
< 0.1%
12.849 1
< 0.1%
12.727 1
< 0.1%

druggable
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size39.7 KiB
0
1319 
1
1223 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2542
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1319
51.9%
1 1223
48.1%

Length

2023-05-22T12:40:10.015534image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-05-22T12:40:10.091275image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
0 1319
51.9%
1 1223
48.1%

Most occurring characters

ValueCountFrequency (%)
0 1319
51.9%
1 1223
48.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2542
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1319
51.9%
1 1223
48.1%

Most occurring scripts

ValueCountFrequency (%)
Common 2542
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1319
51.9%
1 1223
48.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2542
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1319
51.9%
1 1223
48.1%

Interactions

2023-05-22T12:40:04.147761image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:34.420456image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:36.077563image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:37.537993image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:39.075344image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:40.505894image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:42.106232image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:43.559663image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:45.536910image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:47.106209image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:48.627379image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:50.150223image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:51.651988image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:53.054426image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:54.618766image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:56.154978image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:57.563936image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:59.115623image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:00.802967image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:02.627589image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:04.222291image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:34.554103image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:36.149678image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:37.609643image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:39.146354image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:40.589780image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:42.179499image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:43.637575image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:45.638221image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:47.180615image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:48.706934image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:50.222925image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:51.723576image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:53.132308image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:54.703555image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:56.226998image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:57.707701image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:59.192403image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:00.901160image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:02.712188image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:04.293644image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:34.667432image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:36.214738image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:37.676220image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:39.217247image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:40.666402image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:42.248242image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:43.707946image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:45.739550image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:47.249129image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:48.777492image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:50.291058image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:51.789165image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:53.201538image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:54.776213image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:56.291859image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:57.775252image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:59.262871image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:00.997690image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:02.781951image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:04.365531image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:34.757962image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:36.289205image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:37.741382image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:39.282932image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:40.741063image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:42.313908image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:43.780859image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:45.859021image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:47.318083image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:48.848924image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:50.358746image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:51.855579image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:53.273299image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:54.849049image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:56.359559image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:57.844194image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:59.335083image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:01.166394image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:02.851381image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:04.440098image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:34.827842image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:36.364448image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:37.807462image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:39.349243image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:40.822460image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:42.382734image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:43.851066image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:45.957867image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:47.386229image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:48.919205image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:50.426255image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:51.921643image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:53.343782image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:54.921203image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:56.424344image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:57.913789image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:59.445870image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:01.243147image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:02.921205image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:04.592756image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:34.905223image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:36.445908image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:37.885780image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:39.421264image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:40.902372image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:42.455083image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:43.928504image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:46.042843image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:47.460361image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:48.996943image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:50.499116image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:51.992803image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:53.419642image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:54.998515image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:56.496331image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:57.989271image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:59.532014image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:01.327545image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:02.995991image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:04.667948image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:34.977147image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:36.523227image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:37.973235image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:39.490098image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:40.981923image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:42.526751image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:44.040624image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:46.122471image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:47.531484image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:49.071219image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:50.569161image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:52.061529image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:53.492739image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:55.072490image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:56.565570image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:58.059807image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:59.613903image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:01.411060image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:03.075174image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:04.751907image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:35.102515image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:36.604206image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:38.053886image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:39.561215image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:41.061084image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:42.599525image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:44.143040image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:46.193472image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:47.605833image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:49.148237image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:50.642278image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:52.132086image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:53.569441image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:55.150885image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:56.639141image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:58.136012image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:59.708541image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:01.508651image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:03.153859image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:04.826364image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:35.170289image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:36.678353image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:38.127364image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:39.628369image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:41.135421image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:42.669634image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:44.239100image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:46.259014image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:47.673644image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:49.219290image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:50.711420image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:52.199928image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:53.638729image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:55.221430image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:56.704059image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:58.206023image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:59.805245image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:01.585717image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:03.226876image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:04.901385image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:35.259487image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:36.752676image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:38.206387image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:39.705884image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:41.212208image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:42.742516image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:44.323968image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:46.329391image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:47.746187image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:49.298518image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:50.783144image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:52.270322image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:53.717227image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:55.299121image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:56.775771image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:58.282053image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:59.897605image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:01.664030image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:03.303297image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:04.982126image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:35.338309image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:36.829251image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:38.351953image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:39.784593image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:41.294940image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:42.821044image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:44.422250image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:46.405089image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:47.824379image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:49.377513image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:50.860038image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:52.346557image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:53.795885image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:55.384746image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:56.852236image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:58.360819image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:59.987584image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:01.741147image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:03.384838image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:05.056458image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:35.411305image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:36.897215image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:38.424899image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:39.855982image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:41.367488image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:42.891092image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:44.507244image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:46.472188image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:47.894303image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:49.452516image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:50.930153image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:52.414910image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:53.871350image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:55.460678image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:56.920612image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:58.433209image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:00.069685image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:01.817053image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:03.456194image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:05.127990image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:35.479068image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:36.963227image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:38.490561image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:39.921332image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:41.438871image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:42.958036image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:44.603434image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:46.538746image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:47.962947image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:49.522925image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:50.996429image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:52.480973image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:53.940551image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:55.532385image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:56.989548image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:58.502643image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:00.148438image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:01.894979image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:03.526580image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:05.205292image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:35.559330image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:37.036089image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:38.565035image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:39.997718image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:41.582405image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:43.036690image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:44.716750image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:46.612163image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:48.038144image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:49.604893image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:51.074186image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:52.554973image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:54.016966image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:55.613606image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:57.064603image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:58.581594image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:00.250651image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:01.984560image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:03.610761image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:05.287160image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:35.640091image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:37.112765image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:38.640597image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:40.073917image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:41.664817image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:43.117376image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:44.895997image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:46.688951image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:48.118429image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:49.694174image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:51.152836image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:52.633076image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:54.098612image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:55.694458image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:57.141968image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:58.664417image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:00.342887image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:02.086553image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:03.694922image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:05.357127image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:35.708473image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:37.179588image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:38.706270image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:40.139422image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:41.734654image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:43.190690image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:44.981707image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:46.753873image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:48.186002image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:49.766043image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:51.221911image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:52.699125image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:54.168661image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:55.767264image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:57.207891image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:58.736670image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:00.420959image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:02.177858image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:03.765611image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:05.432114image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:35.785603image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:37.253648image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:38.778888image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:40.211083image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:41.809477image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:43.265475image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:45.093566image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:46.824507image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:48.329795image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:49.844235image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:51.295089image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:52.769806image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:54.245254image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:55.846086image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:57.280898image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:58.812635image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:00.500076image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:02.286786image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:03.841219image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:05.506620image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:35.859111image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:37.325836image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:38.854535image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:40.283041image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:41.883370image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:43.340477image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:45.192894image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:46.896976image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:48.406505image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:49.921252image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:51.369195image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:52.842840image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:54.321758image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:55.925168image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:57.353271image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:58.888667image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:00.573822image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:02.382417image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:03.916881image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:05.579650image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:35.929683image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:37.396469image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:38.929010image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:40.354194image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:41.957734image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:43.411143image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:45.287753image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:46.964154image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:48.478265image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:49.995907image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:51.506899image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:52.912260image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:54.395708image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:55.998354image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:57.420773image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:58.961261image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:00.646339image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:02.462213image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:03.993988image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:05.656088image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:36.003921image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:37.466472image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:39.003337image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:40.427584image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:42.030630image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:43.485437image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:45.399285image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:47.035238image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:48.553372image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:50.074003image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:51.579744image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:52.983654image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:54.472676image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:56.077955image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:57.492221image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:39:59.039465image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:00.722048image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:02.548902image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-22T12:40:04.071215image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Missing values

2023-05-22T12:40:05.793389image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
A simple visualization of nullity by column.
2023-05-22T12:40:06.007761image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

seq_nameARNDCEQGHILKMFPSTWYVdruggable
0Negative_00.0007.8430.0000.0009.8043.9221.9611.9610.0003.9227.8437.8433.9225.8820.00013.7257.8439.8049.8043.9220
1Negative_14.2114.7372.1054.2112.6323.6842.1055.7892.1055.26314.7372.1051.57915.2635.78911.5796.3160.5260.5264.7370
2Negative_28.9787.1211.8583.4063.7154.0253.4068.3591.2383.71511.7653.4060.9292.7868.66912.6935.8821.8580.9295.2630
3Negative_30.00017.0730.0002.4392.4397.3174.87817.0732.4392.4392.4390.0004.8780.00012.19512.1952.4397.3170.0002.4390
4Negative_41.7548.7721.7545.2633.5095.2633.5097.0183.5095.26315.7893.5093.5090.0005.26310.5261.7545.2631.7547.0180
5Negative_56.5427.0093.7384.2060.9354.2064.6738.8792.3363.73812.1508.4112.3363.2714.6737.9447.9440.4670.4676.0750
6Negative_64.8080.9623.8463.8462.8854.8084.80810.5774.8085.76914.4234.8081.9234.8083.84611.5380.9620.9623.8465.7690
7Negative_711.29011.2902.4194.0321.6131.6134.83912.9031.6133.22612.0971.6130.0001.6138.8719.6774.8390.8060.0005.6450
8Negative_84.4128.8241.4713.6764.4125.8827.3535.8824.4127.3537.3532.2062.2065.1473.6768.8245.8823.6763.6763.6760
9Negative_98.33310.0000.5565.5563.8894.4446.66713.8892.2220.5564.4442.7782.2222.2228.8898.3332.7786.6670.5565.0000
seq_nameARNDCEQGHILKMFPSTWYVdruggable
1213Positive_12136.8706.4124.2753.5112.4435.9542.4434.8852.1375.9549.0084.1222.9015.3445.9549.4667.9390.7633.6645.9541
1214Positive_12147.0092.6484.0502.6483.1153.8943.2717.7881.4029.81310.2805.1402.4926.2314.0507.6323.5833.8944.0507.0091
1215Positive_12154.9055.5384.4306.1711.7415.5383.4815.3803.3235.6969.6523.1652.0575.2225.0639.0196.1711.7414.5897.1201
1216Positive_12167.4807.2832.5594.1340.1978.6614.7247.0873.1502.95310.8275.5122.9534.7245.5127.2834.3311.5752.5596.4961
1217Positive_12177.5593.6221.5752.2052.5202.0473.6229.6061.4174.72414.3311.7323.9376.1425.1979.2916.1421.4174.0948.8191
1218Positive_12184.8476.9473.5546.6240.9695.9774.0396.1392.9085.0089.2085.9772.5853.3937.10810.0165.6540.6463.5544.8471
1219Positive_12196.1354.5504.3975.0612.0456.0843.2725.5731.5346.95310.5835.1122.7106.9025.0617.6185.7771.6362.4546.5441
1220Positive_122010.1738.7663.1395.0872.1659.6323.3555.1952.7062.81410.6064.1132.1654.1134.2218.2254.9780.8661.1906.4941
1221Positive_12218.3334.1673.1256.9442.0835.9036.2507.9862.7787.9865.2089.0281.7362.7783.4724.5144.1672.4312.7788.3331
1222Positive_122210.1966.2755.0984.7061.1768.2352.7459.4122.3535.88210.1963.9221.5693.9221.1765.0987.0590.3921.9618.6271